Author:
Zhang Feng,Deng Yan,Wang Dong,Wang Shuai
Abstract
AbstractThe present study aimed to construct a pyroptosis-related gene signature in uveal melanoma (UM) patients. Patients from The Cancer Genome Atlas (TCGA) served as the training cohort, whereas patients (GSE22138) from Gene Expression Omnibus (GEO) served as the validation cohort. Using the Kaplan–Meier (KM) method, univariate analysis, and least absolute shrinkage and selection operator (LASSO) Cox regression, A five pyroptosis-related gene signature was constructed in the training cohort. Patients were divided into high- and low-risk groups. Survival analysis showed that patients in the high-risk group had a shorter survival time. Risk and survival analysis, time-independent receiver operating characteristic (ROC) curve analysis and principal component analysis (PCA) validated that the prognostic signature had greater predictive value in both cohorts. Multivariate analysis proved that the risk score was an independent prognostic factor. Functional analysis showed that the expressed genes in the high-risk group were most abundant in immunological repose-related and tumor-related signaling pathways. Single-sample gene-set enrichment analysis (ssGSEA) revealed that the different risk groups were associated with the tumor microenvironment. Moreover, the predictive signature could help patients be better matched to immunotherapy and targeted treatments. In conclusion, the pyroptosis-related gene signature associated with the tumor microenvironment maybe a reliable tool for predicting the prognosis of UM patients.
Funder
National Science Foundation of Shandong Province of China
Publisher
Springer Science and Business Media LLC
Cited by
6 articles.
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